Thanh V. Pham, Anh T. Pham 1 Introduction

Transcription

1 Published in IET Communications Received on 0th May 013 Revised on 1st January 014 Accepted on 3rd January 014 ISSN Performance analysis of amplify decode-and-forward multihop binary phase-shift keying/free-space optical systems using avalanche photodiode receivers over atmospheric turbulence channels Thanh V. Pham, Anh T. Pham Computer Communications Laboratory, University of Aizu, Aizuwakamatsu, Fukushima, Japan Abstract: This study studies the performance of multihop free-space optical systems using the subcarrier binary phase-shift keying modulation over atmospheric turbulence channels. The authors propose a modified relaying strategy, termed amplify decode-and-forward, realised by using avalanche photodiode (APD) receivers. The outage probability of the proposed system is analytically derived considering the atmospheric turbulence and the receiver noise, including APD shot noise and thermal noise. The analytical results are verified by Monte Carlo simulations, and a good agreement between the analytical and simulation results is confirmed. In the authors analysis, they quantitatively discuss the impact of turbulence strength, number of relay nodes, relaying configuration, system bit rate and receiver parameters on the system outage probability. In addition, the optimal value of APD gain for achieving the lowest outage probability in different cases of relaying configuration, number of relays and receiver parameters is also discussed. 1 Introduction Free-space optical (FSO) communications is an optical transmission technology that uses the light signal to transmit data over free space in telecommunications or computer networks. It has recently emerged as one of the important technologies in wireless communications, thanks to its significant advantages of high data rates, ease of deployment, license-free and long-range operation 1, ]. In addition, the FSO communications also offers an effective solution for the spectrum scarcity problem, especially in the wireless-access environment. One of the most challenging issues for the realisation of FSO systems, especially over the long distance (more than km), is the effect of atmospheric turbulence, which is caused by the variation of refractive-index of the air ]. The atmospheric turbulence causes the intensity fluctuation of the received optical signal, which reduces the system performance. Several statistical models have been proposed to describe the atmospheric turbulence in this literature. For the weak-to-moderate turbulence, the log-normal distribution is suitable for modelling the atmospheric channel. On the other hand, the gamma gamma distribution is generally accepted for the moderate-to-strong turbulence. To increase the reliability as well as to achieve a broader coverage of the FSO systems over atmospheric turbulence channels, multihop (or relaying) transmission technique has been proposed as a potential solution 3]. The main idea of this technique is to relay signal from the source to the destination through intermediate terminals called relay nodes; and depending on the structure of relay nodes, there are two relaying strategies, namely: decode-and-forward (DF) and amplify-and-forward (AF) relaying. In the AF relaying, the received signal at each relay node is amplified before it is retransmitted to the following relay node. In case of the DF relaying technique, the received signal is detected and demodulated to recover the original data before it is regenerated for relaying to the next node. There have been recently a number of studies on the analysis of the outage probability of multihop FSO systems 4 7]. For the log-normal channel, Safari and Uysal 4] derived the outage probability of serial and parallel relay-assisted FSO systems for both AF and DF relaying techniques. In addition, Karimi and Nasiri-Kenari 5] presented the outage analysis of parallel relaying with cooperative protocol. The outage analyses of AF and DF relaying systems over the gamma gamma channel were presented in 6 8]. Previous studies reveal that in the FSO communications, because of the complexity and cost of the all-optical amplifying systems 9], the AF relaying is less attractive in comparison with the DF one. In addition, the noise is added to the received signal at each intermediate relay node through transmission path, resulting in the limited transmission distance. The purpose of the DF technique is to eliminate the noise propagation; it therefore greatly improves system performance in comparison with that of the AF technique 4]. On the other hand, it is worth noting that the impact of receiver noise, including the shot 1518

2 noise and thermal noise, is critical in optimising the design of optical systems, and it has been thoroughly studied in single hop FSO systems 10, 11]. However, to the best of our knowledge, it has not been considered in all previous studies of DF relaying systems. In this paper, we therefore study the outage behaviour of the multihop FSO systems considering the impact of both the atmospheric turbulence channel and receiver noise in both destination and relay nodes. In addition, we employ a modified DF relaying with amplification, termed amplify DF (ADF), which is realised by using avalanche photodiode (APD) receivers at the destination and relay nodes. In the ADF relaying, the received signal at each relay node will be amplified and decoded by an APD receiver. The decoded data are then regenerated and forwarded to the following node. The implementation of the proposed ADF systems is basically similar to that of the DF ones; the only difference is that APDs are used instead of p-i-n photodiodes. Besides the proposal of the modified ADF relaying strategy, another key contribution of this paper is the derivation of closed-form expressions of the system outage probability taking into account both atmospheric turbulence Fig. 1 Multihop FSO configurations a Serial configuration b Parallel configuration and receiver noise. It is important to note that all previous studies only assumed that noise was signal-independent (which is not practically realistic) so that the closed-form expression derivation was considerably simpler. In addition, we obtain the closed-form for both serial and parallel configurations over log-normal and gamma gamma channel models for the cases of weak-to-moderate and moderate-to-strong atmospheric turbulences, respectively. Finally, we validate the analytical results by Monte Carlo simulations and a good agreement between the analytical and simulation results is confirmed. The rest of this paper is organised as follows. In Section, we introduce the system model and the serial and parallel relaying configurations. The proposed system using APD receivers and atmospheric turbulence channel models are also described in this section. The outage probability analysis is presented in Section 3. Section 4 presents the numerical results and discussion. Finally, we conclude this paper in Section 5. System descriptions.1 System models We consider a multihop FSO system employing subcarrier binary phase-shift keying modulation (BPSK) signalling, in which there are N relay nodes between the source and the destination nodes. The BPSK signalling is selected thanks to its use of the zero threshold level, which, in comparison with the on off keying, results in the easier signal detection in the presence of atmospheric turbulence 11]. These N nodes can be arranged in either serial or parallel fashion, thus, we have the serial and parallel relaying configurations, as shown in Figs. 1a and b. In both serial and parallel systems, there are three types of nodes: source, destination and relay nodes; and in the ADF mode the architectures of these nodes are illustrated as in Fig., in which APDs are used as photodetector in all DF relay nodes and the destination node. The source node Fig. a Source node b Destination node c Relay nodes Architectures of the source, relay and destination nodes 1519

3 consists of a subcarrier BPSK transmitter, as illustrated in Fig. a. Binary data are first electrically modulated onto a radio frequency (RF) subcarrier by the BPSK modulator, by which bit 0 and bit 1 are represented by two different phases 180 apart. In the optical intensity modulator, the electrical BPSK signal is used to modulate the intensity of the light source, that is, a laser beam. The direction and the size of the laser beam are determined by the collimator or telescope in the transmitter. At the destination node, as in Fig. b, there is a subcarrier BPSK receiver. The incoming optical field from the telescope is converted into an electrical signal by the APD. The transmitted data are then recovered by using a standard RF coherent demodulator. At each relay node, there is a pair of subcarrier BPSK transmitter and receiver, as shown in Fig. c. The received optical signal is detected, amplified by APD and the data are recovered (i.e. decoded). The decoded data are then re-encoded at the subcarrier BPSK transmitter and relayed to the following node or the destination depending on the configuration (serial or parallel) and the position of the relay node.. Channel models We first examine an FSO channel between two terminals A and B. The received signal P(t) at terminal B can be expressed as P(t) = ax (t)p 0 (t) (1) where a, X(t) and P 0 (t) denote the channel loss, the random process representing the scintillation caused by atmospheric turbulence and the transmitted signal power, respectively. The channel loss because of both molecular absorption and aerosol scattering suspended in the air, is given by 1] a = A r p(fl/) exp( b nl) () where A r, f, l and b n denote the area of the receiver aperture, the optical beam s divergence angle in radians, the channel distance between two terminals and the atmospheric extinction coefficient, respectively. The irradiance fluctuations represent the signal scintillation caused by the atmospheric turbulence. When the turbulence is weak, it is generally accepted that X(t) could be modelled as a random process with log-normal distribution. Assuming that the average of the random process X(t) is normalised to unity, its probability density function (pdf) is given by 1 f X (x) = p ss x exp (ln x + s s /) ] s s Here, s s is the log intensity variance depending on the channel s characteristics with respect to the distance of two terminals and is given by 13] (see (4)) in which, d = kd /4l, and k =π/λ is the optical wave number. The parameter s R is the Rytov variance, and (3) assuming plane wave propagation, it is given by s R = 1.3C n k 7/6 l 11/6 (5) where Cn is the altitude-dependent index of the refractive structure parameter determining turbulence strength. When turbulence strength becomes stronger (typically, when the value of Cn is > ), X(t) can be modelled as a random process with gamma gamma distribution and its pdf is given by 13] f X (x) = (ab)(a+b/) G(a)G(b) x (a+b/) 1 K a b ( abx) (6) Here Γ(.) is the gamma function, and K α β (.) is the modified Bessel function of the second kind and order α β. Beside the link length l, α and β are given by 13] { ] } 0.49s 1 R a = exp ( s 1/5 1 (7) R ) 7/6 { ] } 0.51s 1 R b = exp ( s 1/5 1 (8) R ) 5/6 where s R with respect to the distance l between two terminals is given in (5)..3 Single hop FSO system using APD receiver Now we consider a single hop FSO system using APD receiver and subcarrier BPSK signalling. In such system, the received optical power P(t) can be written as P(t) = ax (t) P s 1 + m cos(pf ct + b k p)] (9) where P s is the average transmitted power, m is the modulation index, f c is the subcarrier frequency and b k {0, 1} denotes the binary data signal. As the temporal correlation time of the atmospheric scintillation process is on the order of several milliseconds, which is much longer than a bit duration (less than a microsecond when the bit rate is higher than tens of Mb/s), the dc term ax(t)p s / can be filtered out by a bandpass filter. The output electrical signal of the APD therefore can be expressed as I(t) = m< g P s ax (t)cos(pf ct + b k p) + n(t) (10) where <, g and n(t) denote the responsivity, the average APD gain and the receiver noise, respectively. For BPSK demodulation, by employing a coherent detection, the s s = exp ] 0.49s s ( d s (1/5) R ) ss (7/6) ( d + 0.6d s (1/5) R ) (5/6) 1 (4) 150

4 output signal r(t) can be written as r(t) = I(t)cos(pf c t) 1 = 4 m< gp sax (t) + j(t) in the mark state 1 4 m< gp sax (t) + j(t) in the space state (11) relay hops, which equals to N + 1 or N for the serial or parallel configuration, respectively. Now consider an FSO hop between two consecutive nodes ith and jth. The electrical signal after APD detection at the jth node can be written as r j = r m j, r s ] j ] where ξ(t) is the APD receiver noise including APD shot noise, thermal noise and dark current. Assuming the dark current is negligible, ξ(t) can be given by j(t) = i Th (t) + i Sh (t) (1) where i Th (t) and i Sh (t) are the thermal noise and shot noise, respectively. The thermal noise can be modelled as a zero-mean stationary Gaussian random process whose variance is given by s Th = 4k BT R L F n Df (13) in which k B, T, R L, F n and Δf denote the Boltzmann constant, the absolute temperature of receiver, the APD s load resistance, the amplifier noise figure and the effective noise bandwidth, respectively 14]. The effective noise bandwidth depends on the bit rate, the shapes of received and equalised pulses, and the design of the receiver. We choose the typical Δf = R b /, where R b is the system bit rate. Considering the APD shot noise, the scintillation causes the fluctuation in the received optical signal and it also leads to uncertainty in the shot noise variance. Again, as the temporal correlation time is much longer than a bit duration, the scintillation could be considered to be constant during the bit duration. i Sh (t) therefore can be also modelled as a stationary Gaussian random process whose variance is given by 14] ( s Sh = q g F A < m ) 4 P sax Df (14) where q is the electron charge and F A is the exceed noise factor and given by F A = k A g + (1 k A )( (1/ g)), where k A is the ionisation factor. Finally, as the shot noise and thermal noise are independent Gaussian random processes, the total variance of APD receiver noise can be obtained by adding these individual variances as s = s Sh + s Th..4 ADF multihop FSO system using APD receivers In the analysis, we use the indexes 0 and N + 1 for indicating the source and destination nodes, respectively; the indexes from 1,, to N are used for the N relay nodes. We also assume that the APD receiver parameters at each node are the same, and the atmospheric fluctuations at all hops are independent and identically distributed. For both relaying configurations, it is assumed that total transmitted power is allocated equally on each hop. The transmitted power at each relay hop, denoted as P s, is therefore given by P s = P t N r (15) where P t is the total transmitted power. N r is the number of = 1 4 m< gp sa i, j x i, j + n m j, 1 4 m< gp sa i, j x i, j + n s j (16) where rj m and rj s are the received signal in the mark and the space states, respectively. a i,j and x i, j represent the channel loss and the irradiance fluctuation of the hop between nodes ith and jth, as in the above analysis. n m j and n s j denote the receiver noise corresponding to the mark and space states at the jth node. Note that, n m j and n s j have the same variance s j, which is given by s j = 4k BT R L ( F n Df + q g F A < m ) 4 P sa i, j x i, j Df (17) (1) Serial configuration: In serial relaying, the received signal at the jth node ( j =1,,, N + 1) is given by r j = rj m, rj s ] 1 = 4 m< gp sa j 1, j x j 1, j + n m j, (18) 1 4 m< gp sa j 1, j x j 1, j + n s j In this case, the variance of the receiver noises in the mark and space states, n m j and n s j, is also given as (17) with i = j 1. () Parallel configuration: In this case, the source transmits signal to each relay node directly. The received signal at the jth relay node ( j =1,,, N) is therefore given by r j = r m j, r s ] j 1 = 4 m< gp sa 0, j x 0, j + n m j, (19) 1 4 m< gp sa 0, j x 0, j + n s j The noise variances of n m j and n s j is given as (17) with i =0. In the parallel relaying, the system can operate even when not all of the relay nodes successfully decode the received signal. Denote S as the decoded set, which is the set of relay nodes that decode the received signal successfully. The received signal at the destination thus can be obtained by adding individuals transmitted signal from the decoded set as r N+1 = rn+1, m r s ] N+1 1 = 4 m< gp s (a is i, N+1x i, N+1 ) + n m N+1, 1 4 m< gp (0) (a is i, N+1x i, N+1 ) + n s N+1 The variance of the receiver noise at the destination in the 151

5 mark and space states, denoted as s N+1, therefore can be derived as s N+1 = 4k BT F R n Df L ( ) + q g F A < m 4 P s a i, N+1 x i, N+1 Df (1) 3 Outage analysis In the proposed ADF systems, all relay nodes decode the received signal before regenerating and forwarding it to the next one, the calculation of outage probability at each intermediate hop is necessary. For each hop, outage is defined as state at which signal cannot be decoded with an arbitrarily low error probability for a given bit rate, for example, R b ; in other words, the outage happens when the instantaneous signal-to-noise ratio (SNR) falls below a threshold value, denoted as γ th, at which the equivalent instantaneous capacity is equal to R b. In this paper, we assume that the same γ th value is applied for all hops. When outage happens, the corresponding node is failed and it will stop forwarding signal to the next one. For a BPSK/ FSO link, the outage probability of the link can be expressed as is P out (g) = Pr(g, g th ) () Here, γ is the instantaneous electrical SNR at the receiver, which can be given as g = (mm m s ) s (3) where σ is the noise variance of receiver noise, μ m and μ s are the means of the received signal at the mark and space states as mentioned in (11), respectively. From (16), (17) and (3), the SNR of the hop between two consecutive nodes ith and jth can be expressed by g i, j = (m< gp sa i, j x i, j ) 8s j (4) By denoting F X (x) as the cumulative distribution function (cdf) of the random variable X, outage probability of this hop can be expressed as ( 4N out (g i, j ) = F r g th C + ) D X P hop Aa i, j (5) where Δ is defined by D = (4N r g th C) + 8N r g th BA (6) In (5) and (6), A, B and C are defined in Appendix. The proof of (5) derivation also can be found in this Appendix. 3.1 Serial configuration In the serial relaying, an outage occurs if any one of the intermediate links breaks down. The outage probability of the system therefore can be given by P out = Pr ( ) N+1 = 1 Pr = 1 N+1 Inserting (5) into (7) yields {g j 1, j, g th } ( ) N+1 {g j 1, j. g th } 1 P hop out (g j 1, j )] (7) ( P out = 1 N+1 4(N + 1)g 1 F th C + )] D s X Aa j 1, j (8) where Δ s is given by (6) as N r = N + 1 for the case of serial relaying. (1) Log-normal channel: In case of log-normal channel, (8) can be rewritten as (see (9)) where s (j 1) s is the deviation of atmospheric turbulence of the hop connecting the ( j 1)th and jth relay nodes. Q(x) = (1/ 1 p ) exp( (t /)) dt is the Gaussian x Q-function. () Gamma gamma channel: The cdf of the gamma gamma distribution with two parameters α, β defined in (7) and (8) is given by 15] (see (30)) where G m, n p, q.] is the Meijer s G-function 16]. By substituting (30) into (8), the closed-form expression of the outage probability P out can be derived. 3. Parallel configuration In the parallel relaying, the outage occurs in one of the hops between the source and relay hops may not result in an outage of the system. In this case, an outage happens when either the decoded set S is empty or the multiple-input single-output (MISO) link between the relay nodes and the destination ( P out = 1 N+1 1 Q ln(aa j 1, j/4(n + 1)g th C + )] D s) s(j 1) s s (j 1) s (9) F X (x) = (abx)(a+b/) G(a)G(b) G a b, 1 a + b b a, a + b abx (30) 15

6 fails. From (0) and (1), the SNR at the destination can be derived as g S = (m< gp s is a i, N+1x i, N+1 ) 8s N+1 (31) Making the change of random variable z S = is a i, N+1x i, N+1 and using the definitions of A, B and C, the outage probability of this MISO link can be given by ( 4(N)g th C + ) out (g S ) = F ZS A P MISO (3) where F ZS (.) is the cdf of random variable z S, Δ p is defined as (6) as N r =N for the case of parallel relaying. Note that there are N possibilities of decoded set. We denote W n as the nth set and let Pr(W n ) be the probability of the event {S = W n }. The outage probability of the system can be expressed as P out = N n=1 P MISO out (g Wn )Pr(W n ) (33) Assuming that the jth relay node belongs to W n, implying that no outage between the source and jth node. We therefore have Pr(j W n ) = 1 P hop out (g 0, j ), where P hop out (g 0, j ) is the outage probability of the jth hop, which is given in (5). For the jth relay node, ( which ) does not belong to W n, obviously, we have Pr j Ó W n = P hop out (g 0, j ). As a result, we could obtain Pr(W n ) = ( 1 P hop out (g 0, j ) ) out (g 0, j ) (34) jw n jów n P hop By substituting (3), (34) into (33), the outage probability of the parallel relaying can be expressed a (see (35)) (1) Log-normal channel: In case X is the log-normal distribution, the exact distribution of z S is unknown. However, there have been several methods for approximating the sum of log-normal random variables 17, 18]. In this study, we employ the well-known Fenton Wilkinson method 19], in which, the approximated logarithm mean m ZS and logarithm variance s Z S of z S can be derived as m ZS = ln a i, N+1 s Z S is (36) ( ) s is a i, N+1 e s s (l i, N+1 ) 1 Z S = ln 1 + ( is a ) i, N+1 (37) Therefore, the approximation of the outage probability can be derived as (see (38)) where s (j) s is the deviation of atmospheric turbulence of the hop connecting the source and the jth relay node. () Gamma gamma channel: In 0], it is shown that the sum of gamma gamma random variables can be approximated efficiently by a gamma random variable. We will apply this result to approximate the random variable z S. Assuming that z S is approximated by a gamma random variable Ψ S, the scale parameter θ S and shape parameter k S of Ψ S are defined by u S = is K S i a i, N+1 + is is a i, N+1 js j.i a i, N+1 a j, N+1 (1 + 1 i )a i, N+1 (39) is is k S = a i, N+1 (40) u S where K Si is given by K Si = a (i) + 1 b (i) + 1 a (i) b (i) (41) where α (i), β (i) are the parameters of gamma gamma distribution for atmospheric turbulence of the hop connecting the ith relay node and the destination. The adjustment parameters {ε i } can be chosen in the range 1; K Si 1]. The outage probability of the MISO link therefore can be derived as ( ( Pout MISO (g S ) 1 G(k S ) F k 4(N)g th C + )) S, (4) Au S P out = N n=1 ( ( ) ) 4(N)g thc + 1 F X ( ) ( 4(N)g thc + 4(N)g th C + ) F Aa X F jw n 0, j Aa ZWn jów 0, j A n (35) P out N n=1 ( ln Aa 0, j /4(N)g th C + ) 1 Q jw n s (j) s ( ln A/4(N)g th C + ) + m ZWn Q s ZWn s(j) s ( ln Aa 0, j /4(N)g th C + ) Q jów n s (j) s s(j) s (38) 153

7 where F(w, x) = x 0 e t t w 1 dt is the lower-incomplete gamma function. By integrating (30), (4) into (35), we have the closed-form expression that approximates the outage probability for the case of the parallel relaying. 4 Numerical results and discussion For analytical results and simulation, the turbulence strength C n is set to for log-normal channel and for gamma gamma channel, and the distance from the source to the destination is L = km. In the serial configuration, the distances between any two consecutive nodes are assumed to be equal. In the parallel configuration, the relay nodes are placed on the halfway point, that is, the point at which the distances from the source to relay nodes and from relay nodes to the destination are the same. In addition, for the sake of simplicity, we assume that these distances are equal to L/. For the FSO link, the atmospheric extinction coefficient β ν = 0.1 db/km, the diameter of the receiver s aperture D = 0.03 m, the angle of divergence is chosen to be 10 3 radian and SNR threshold value is 0 dbm. Unless otherwise noted, we use the system bit rate R b = Gb/s, the receiver noise temperature T = 300 K and the optical wavelength λ = 1550 nm. Other system parameters are: the modulation index m = 1, the APD responsivity < = 1, the APD load resistance R L = 1000 Ω, the amplifier noise figure F n = and the ionisation factor k A = 0.7 for a typical InGaAs APD. Furthermore, for a fair comparison between different systems with different configurations and different numbers of relay nodes, we analyse the outage probability under a constraint on the total transmitted power, that is, as the number of relays increases, power allocated to each hop will be decreased accordingly. 4.1 Serial configuration Fig. 3 shows the outage probability of serial relaying against the total transmitted power for both log-normal and gamma gamma channels with different numbers of relay nodes. The average APD gain is set to 35. It is observed that an increase in the number of relay nodes results in a better performance, that is, lower-outage probability, in both cases of atmospheric turbulence channels. In case of log-normal channel, at the outage probability of 10 6, the power gain compared with direct transmission, when the numbers of relay nodes N = 1, and 3 are 1, 16 and 19 db, respectively. In case of gamma gamma channel, the improvements are 35, 44 and 50 db for N = 1, and 3, respectively. Monte Carlo simulations are also used to verify the analytical results and the good agreement between the simulation and analytical results for both turbulence channel models confirms the validity of the analysis. In Fig. 4, the outage probability is represented with respect to the system bit rate for different numbers of relay nodes. The total transmitted power is fixed at 15 dbm and the average APD gain of 35 is selected. It is seen that the relay transmission could significantly increase the system bit rate. For example, at the outage probability of 10 6 with turbulence strength C n = , the -node relaying system could support the bit rate of higher than. Gbps, whereas it is not able to do so with the direct or 1-node relaying system. It is also seen that the outage probability is getting worst drastically as the bit rate increases, especially in the strong turbulence conditions. For example, when N = 1 and C n = , the outage probability goes up from 10 6 to 10 when bit rate increases from 0.5 to 1.5 Gbps. Fig. 5 demonstrates the relationship between the outage probability and the average APD gain with two values of turbulence strength corresponding to the log-normal and gamma gamma channels. Obviously, the system outage performance is greatly improved as the number of relay nodes increases. In addition, we also see that, similar to the case of single hop, the performance of the multihop system can also be optimised by selecting an appropriate value of APD gain. Furthermore, the optimal gain, under the assumption of the same APD receiver for all nodes, is almost unchanged for different numbers of nodes and it is close to 38 in case of InGaAs APD receiver in both of Fig. 3 Outage probability against total transmitted power P t in cases of log-normal and gamma gamma channels and g = 35 Analytical and Monte Carlo simulation results Fig. 4 Outage probability against bit rate with P t = 15 dbm, g = 35 for different numbers of relay nodes and turbulence strengths 154

8 Fig. 5 Outage probability against average APD gain for log-normal and gamma gamma channels when P t = 15 dbm for different numbers of relay nodes and turbulence strengths log-normal and gamma gamma channels. This is because of two reasons. This is because the value of optimal gain is mainly determined by AParameters, especially the exceed noise factor F A 14]. 4. Parallel configuration This section focuses on the outage analysis for the parallel configuration. Fig. 6 shows the outage probability of the parallel relaying system against the total transmitted power for log-normal and gamma gamma channels. Similar to the case of serial configuration, the analytical results are also confirmed by the Monte Carlo simulations. It is seen that using the multihop system also improves the outage performance. However, unlike the serial relaying, the increase of the number of relay nodes in the parallel system does not always result in better performance. In particular, when the total transmitted power is smaller than 7 dbm in case of log-normal channel, at the outage probability of 10 6, when N increases from 1 to then 3, the additional required transmitted powers are about 1 db for each increase. The improvement when N increases can be seen again when the total transmitted power is high enough. This result is logical as when N increases, the transmitted power for each hop is deceased. However, unlike the serial relaying, the increase of N does not result in shorter transmission distance of a hop (and it is the same as L/). As a result, when the total transmitted power is not high, the increase of N results in worst outage performance in each hop, especially the hops from the source to the relay nodes. Consequently, the overall performance of the system is degraded. It is therefore recommended that for parallel relaying, the number of relay nodes should not be higher than three. In addition, when the total transmitted power is limited the serial relaying is more favourable, especially in the presence of strong turbulence. Next, we consider the impact of the number of relay nodes on the selection of the optimal APD gain for log-normal and gamma gamma channels in Fig. 7. We also assume that the APD receivers at the destination and relays nodes have the same parameters. Again, it is confirmed that the increase in the number of relay nodes does not result in the performance improvement in case of weak turbulence, as shown in Fig. 6. In addition, with the similar reason to that of the serial configuration, the optimal gain is almost the same for different systems with different numbers of relays. Finally, in Fig. 8, we investigate the maximum bit rate at a given outage probability for different turbulence strengths. The total transmitted power P t = 5 dbm is set, average APD gain g = 35 and the number of relay nodes is from 1 to 3. It is also seen that the outage performance is greatly improved in the multihop systems, especially in case of weak turbulence. In addition, similar to serial relaying systems, the increase of the number of relay nodes results in the higher outage probability when the turbulence is Fig. 6 Outage probability against total transmitted power in cases of log-normal and gamma gamma channels when g = 35 Analytical and Monte Carlo simulation results Fig. 7 Outage probability against average APD gain when P t = 10 dbm for different turbulence strengths and numbers of relay nodes 155

9 Fig. 8 Outage probability against bit rate for different turbulence strengths when P t = 5 dbm, g = 35 with different numbers of relay nodes weak (i.e. C n = in this figure). In case of strong turbulence, it is seen that the outage probability is improved as the number of relay nodes increases. 5 Conclusions We have proposed and analysed the performance of ADF multihop FSO systems using the subcarrier BPSK signalling and APD receivers for serial and parallel configurations over both log-normal and gamma gamma turbulence channels. The closed-form expressions of the outage probability were analytically derived taking into account both the atmospheric turbulence and the receiver noise, which includes the APD shot noise and thermal noise. The analytical results were confirmed by Monte Carlo simulations. It was seen that the outage performance was significantly improved in both relaying configurations in comparison with that of the direct transmission. In the parallel relaying however, the increase in the number of relay nodes did not always result in the better performance, especially when the total transmitted power is low. The serial relaying was thus more favourable; and with a proper selection of the number of relay nodes, good outage performance could be achieved at relatively low powers, even in the presence of strong turbulence. The selection of the APD gain also greatly affected the outage probability of the system; however, it was found that the optimal APD gain was almost unchanged in both relaying configurations with different numbers of relays. 6 References 1 Willebrand, H., G-human, B.S.: Free-space optics: enabling optical connectivity in today s networks (Sams Publishing, Indianapolis, Indiana, 001) Ghassemlooy, Z., Popoola, W.O., Rajbhandari, S.: Optical wireless communications system and channel modelling with matlab (CRC publisher, USA, 01) 3 Acampora, A.S., Krishnamurthy, S.V.: A broadband wireless access network based on mesh-connected free-space optical links, IEEE Pers. Commun., 1991, 6, (5), pp Safari, M., Uysal, M.: Relay-assisted free-space optical communication, IEEE Trans. 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Wireless Communications and Networking Conf. (WCNC), 009, pp ElBatt, T., Izadpanal, H.: Design aspects of hybrid RF/free space optical wireless networks. IEEE BroadBand Communications for the Internet Era Symp., 001, pp Appendix: Proof of (5) Let us define A = (m< gp t ), B =(4k B T/R L )F n Δf, C = q g F A <((m/4)p t )Df and replace P s =(P t /N r ) into (4), it can be re-written as Aa i,jx i,j g i,j = 8Nr B + 8N r Ca i,j x i,j (43) Replacing γ i, j into (), the outage probability of the relay hop between nodes ith and jth can be expressed as ( out (g i,j ) = Pr x i,j, 4N rg th C + ) D P hop Aa i,j (44) The outage probability of the hop can be therefore derived as in (5) 156